Feasibility Study of a Socially Assistive Humanoid Robot for Guiding Elderly Individuals during Walking

The impact of the world-wide ageing population has commenced with respect to society in developed countries. Several researchers focused on exploring new methods to improve the quality of life of elderly individuals by allowing them to remain independent and healthy to the maximum possible extent. For example, new walking aids are designed to allow elderly individuals to remain mobile in a safe manner because the importance of walking is well-known. The aim of the present study involves designing a humanoid robot guide as a walking trainer for elderly individuals. It is hypothesized that the same service robot provides an assistive and social contribution with respect to interaction between elderly users by motivating them to walk more and simultaneously provides assistance, such as physical assistance and gait monitoring, while walking. This study includes a detailed statement of the research problem as well as a literature review of existing studies related to walking companion robots. A user-centred design approach is adopted to report the results of the current first feasibility study by using a commercially available humanoid robot known as Pepper developed by Softbank-Aldebaran. A quantitative questionnaire was used to investigate all elements that assess intrinsic motivation in users while performing a given activity. Conversely, basic gait data were acquired through a video analysis to test the capability of the robot to modify the gait of human users. The results in terms of the feedback received from elderly subjects and the literature review improve the design of the walking trainer for elderly individuals

Estratégias de controle de trajetórias para cadeira de rodas robotizadas

Orientador: Eleri CardozoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Desde os anos 80, diversos trabalhos foram publicados com o objetivo de propor soluções alternativas para usuários de cadeira de rodas motorizadas com severa deficiência motora e que não possuam capacidade de operar um joystick mecânico. Dentre essas soluções estão interfaces assistivas que auxiliam no comando da cadeira de rodas através de diversos mecanismos como expressões faciais, interfaces cérebro-computador, e rastreamento de olho. Além disso, as cadeiras de rodas ganharam certa autonomia para realizar determinadas tarefas que vão de desviar de obstáculos, abrir portas e até planejar e executar rotas. Para que estas tarefas possam ser executadas, é necessário que as cadeiras de rodas tenham estruturas não convencionais, habilidade de sensoriamento do ambiente e estratégias de controle de locomoção. O objetivo principal é disponibilizar uma cadeira de rodas que ofereça conforto ao usuário e que possua um condução segura não importando o tipo de deficiência do usuário. Entretanto, durante a condução da cadeira de rodas, o desalinhamento das rodas castores podem oferecer certo perigo ao usuário, uma vez que, dependendo da maneira em que elas estejam orientadas, instabilidades podem ocorrer, culminando em acidentes. Da mesma forma, o desalinhamento das rodas castores é considerado um dos principais causadores de desvios de trajetória que ocorrem durante a movimentação da cadeira de rodas, juntamente com diferentes distribuições de pesos ou diferentes atritos entre as rodas e o chão. Nesta dissertação, é considerado apenas o desalinhamento das rodas castores como único causador de desvio de trajetória da cadeira de rodas e, dessa forma, são propostas soluções que possam reduzir ou até mesmo eliminar o efeito deste desalinhamento. Com a implementação das melhores soluções desenvolvidas neste trabalho, é possível fazer com que diversas interfaces assistivas que têm baixa taxa de comandos possam ser utilizadas, uma vez que o usuário não precisa, constantemente, corrigir o desvio da trajetória desejada. Ademais, é elaborado um novo projeto de cadeira de rodas "inteligente" para a implementação das técnicas desenvolvidas neste trabalhoAbstract: Since the 1980s several works were published proposing alternative solutions for users of powered wheelchairs with severe mobility impairments and that are not able to operate a mechanical joystick. Such solutions commonly focus on assistive interfaces that help commanding the wheelchair through distinct mechanisms such as facial expressions, brain-computer interfaces, and eye tracking. Besides that, the wheelchairs have achieved a certain level of autonomy to accomplish determined tasks such as obstacle avoidance, doors opening and even path planning and execution. For these tasks to be performed, it is necessary the wheelchairs to have a non conventional designs, ability to sense the environment and locomotion control strategies. The ultimate objective is to offer a comfortable and safe conduction no matter the user's mobility impairments. However, while driving the wheelchair, the caster wheels' misalignment might offer risks to the user, because, depending on the way they are initially oriented, instabilities may occur causing accidents. Similarly, the caster wheels' misalignment can be considered, among others like different weight distribution or different friction between wheel and floor, one of the main causes of path deviation from the intended trajectory while the wheelchair is moving. In this dissertation, it is considered the caster wheels' misalignment as the unique generator of wheelchair path deviation and, therefore, it is proposed different solutions in order to reduce or even eliminate the effects of the misalignment. The implementation of the best solutions developed in this work allows assistive interfaces with low rate of commands to be widespread, once the user does not need to, constantly, correct path deviation. Additionally, a new smart wheelchair project is elaborated for the implementation of the techniques developed in this workMestradoEngenharia de ComputaçãoMestre em Engenharia Elétrica88882.329382/2019-01CAPE

Exploring Powered Wheelchair Users and Their Caregivers’ Perspectives on Potential Intelligent Power Wheelchair Use: A Qualitative Study

Power wheelchairs (PWCs) can have a positive impact on user well-being, self-esteem, pain, activity and participation. Newly developed intelligent power wheelchairs (IPWs), allowing autonomous or collaboratively-controlled navigation, could enhance mobility of individuals not able to use, or having difficulty using, standard PWCs. The objective of this study was to explore the perspectives of PWC users (PWUs) and their caregivers regarding if and how IPWs could impact on current challenges faced by PWUs, as well as inform current development of IPWs. A qualitative exploratory study using individual interviews was conducted with PWUs (n = 12) and caregivers (n = 4). A semi-structured interview guide and video were used to facilitate informed discussion regarding IPWs. Thematic analysis revealed three main themes: (1) "challenging situations that may be overcome by an IPW" described how the IPW features of obstacle avoidance, path following, and target following could alleviate PWUs' identified mobility difficulties; (2) "cautious optimism concerning IPW use revealed participants" addresses concerns regarding using an IPW as well as technological suggestions; (3) "defining the potential IPW user" revealed characteristics of PWUs that would benefit from IPW use. Findings indicate how IPW use may help overcome PWC difficulties and confirm the importance of user input in the ongoing development of IPWs

Assistive Navigation Using Deep Reinforcement Learning Guiding Robot With UWB/Voice Beacons and Semantic Feedbacks for Blind and Visually Impaired People

Facilitating navigation in pedestrian environments is critical for enabling people who are blind and visually impaired (BVI) to achieve independent mobility. A deep reinforcement learning (DRL)–based assistive guiding robot with ultrawide-bandwidth (UWB) beacons that can navigate through routes with designated waypoints was designed in this study. Typically, a simultaneous localization and mapping (SLAM) framework is used to estimate the robot pose and navigational goal; however, SLAM frameworks are vulnerable in certain dynamic environments. The proposed navigation method is a learning approach based on state-of-the-art DRL and can effectively avoid obstacles. When used with UWB beacons, the proposed strategy is suitable for environments with dynamic pedestrians. We also designed a handle device with an audio interface that enables BVI users to interact with the guiding robot through intuitive feedback. The UWB beacons were installed with an audio interface to obtain environmental information. The on-handle and on-beacon verbal feedback provides points of interests and turn-by-turn information to BVI users. BVI users were recruited in this study to conduct navigation tasks in different scenarios. A route was designed in a simulated ward to represent daily activities. In real-world situations, SLAM-based state estimation might be affected by dynamic obstacles, and the visual-based trail may suffer from occlusions from pedestrians or other obstacles. The proposed system successfully navigated through environments with dynamic pedestrians, in which systems based on existing SLAM algorithms have failed

A Systematic Review of Adaptivity in Human-Robot Interaction

As the field of social robotics is growing, a consensus has been made on the design and implementation of robotic systems that are capable of adapting based on the user actions. These actions may be based on their emotions, personality or memory of past interactions. Therefore, we believe it is significant to report a review of the past research on the use of adaptive robots that have been utilised in various social environments. In this paper, we present a systematic review on the reported adaptive interactions across a number of domain areas during Human-Robot Interaction and also give future directions that can guide the design of future adaptive social robots. We conjecture that this will help towards achieving long-term applicability of robots in various social domains

模倣学習を用いた両腕ロボット着衣介助システムのデザインと開発

The recent demographic trend across developed nations shows a dramatic increase in the aging population and fallen fertility rates. With the aging population, the number of elderly who need support for their Activities of Daily Living (ADL) such as dressing, is growing. The use of caregivers is universal for the dressing task due to the unavailability of any effective assistive technology. Unfortunately, across the globe, many nations are suffering from a severe shortage of caregivers. Hence, the demand for service robots to assist with the dressing task is increasing rapidly. Robotic Clothing Assistance is a challenging task. The robot has to deal with the following two complex tasks simultaneously, (a) non-rigid and highly flexible cloth manipulation, and (b) safe human-robot interaction while assisting a human whose posture may vary during the task. On the other hand, humans can deal with these tasks rather easily. In this thesis, a framework for Robotic Clothing Assistance by imitation learning from a human demonstration to a compliant dual-arm robot is proposed. In this framework, the dressing task is divided into the following three phases, (a) reaching phase, (b) arm dressing phase, and (c) body dressing phase. The arm dressing phase is treated as a global trajectory modification and implemented by applying the Dynamic Movement Primitives (DMP). The body dressing phase is represented as a local trajectory modification and executed by employing the Bayesian Gaussian Process Latent Variable Model (BGPLVM). It is demonstrated that the proposed framework developed towards assisting the elderly is generalizable to various people and successfully performs a sleeveless T-shirt dressing task. Furthermore, in this thesis, various limitations and improvements to the framework are discussed. These improvements include the followings (a) evaluation of Robotic Clothing Assistance, (b) automated wheelchair movement, and (c) incremental learning to perform Robotic Clothing Assistance. Evaluation is necessary for our framework. To make it accessible in care facilities, systematic assessment of the performance, and the devices’ effects on the care receivers and caregivers is required. Therefore, a robotic simulator that mimicks human postures is used as a subject to evaluate the dressing task. The proposed framework involves a wheeled chair’s manually coordinated movement, which is difficult to perform for the elderly as it requires pushing the chair by himself. To this end, using an electric wheelchair, an approach for wheelchair and robot collaboration is presented. Finally, to incorporate different human body dimensions, Robotic Clothing Assistance is formulated as an incremental imitation learning problem. The proposed formulation enables learning and adjusting the behavior incrementally whenever a new demonstration is performed. When found inappropriate, the planned trajectory is modified through physical Human-Robot Interaction (HRI) during the execution. This research work is exhibited to the public at various events such as the International Robot Exhibition (iREX) 2017 at Tokyo (Japan), the West Japan General Exhibition Center Annex 2018 at Kokura (Japan), and iREX 2019 at Tokyo (Japan).九州工業大学博士学位論文 学位記番号：生工博甲第384号 学位授与年月日：令和2年9月25日1 Introduction|2 Related Work|3 Imitation Learning|4 Experimental System|5 Proposed Framework|6 Whole-Body Robotic Simulator|7 Electric Wheelchair-Robot Collaboration|8 Incremental Imitation Learning|9 Conclusion九州工業大学令和2年

高齢者とともに歩行する社会的支援ヒューマノイドに関する研究

筑波大学 (University of Tsukuba)201

"I can't get round": Recruiting Assistance in Mobile Robotic Telepresence

Via audiovisual communications and a controllable physical embodiment, Mobile Robotic telePresence (MRP) systems aim to support enhanced collaboration between remote and local members of a given setting. But MRP systems also put the remote user in positions where they frequently rely on the help of local partners. Getting or 'recruiting' such help can be done with various verbal and embodied actions ranging in explicitness. In this paper, we look at how such recruitment occurs in video data drawn from an experiment where pairs of participants (one local, one remote) performed a timed searching task. We find a prevalence of implicit recruitment methods and outline obstacles to effective recruitment that emerge due to communicative asymmetries that are built into MRP design. In a future where remote work becomes widespread, assistance through remote work technology like MRPs needs close examination at a fundamental interactional level, taking into account how communicative asymmetries are at play in everyday use of such technologies